0.3.0 — outcome tracking (V4)

• bench: internal benchmark suite (bench/run_bench.py) — engine-overhead
  medians against a zero-latency scripted model, the acceptance eval, and the
  robustness tier at --s4-samples 50 with duplicate-shape classification
  (the value-equivalence T0 measurement), recorded per-release to
  bench/results.jsonl with a --compare regression gate. Now part of the
  maintainer release checklist. See bench/README.md.

• mcp 2.0 compat: the MCP SDK 2.0.0 renamed FastMCP to MCPServer
  (same decorator API) — veracium-mcp now imports whichever the installed
  SDK provides, so mcp>=1.0 stays the supported range on both majors.

• outcome tracking (V4): co-designed with the first production consumer —
  record_outcome() records uses and judgments of facts as kind="outcome"
  episodes (the source of truth) with derived edge counters
  (times_used/outcome_counts/last_outcome); judgments upgrade the
  matching use in place via (edge_id, evidence_ref). Vocabulary:
  unreviewed/confirmed/corrected (human) /challenged/concurred
  (LLM judge), actor rules enforced. Edge-blind by design: record_outcome
  never supersedes facts; the explicit fact-level correct() verb supersedes
  with reason "corrected". challenged reuses the possibly-stale flag;
  counters render into recall as information, never gating; outcome episodes
  are excluded from the narrative recall window and from LLM consolidation.
  Portability format v2 ("record" marker; v1 imports unchanged). Neither
  verb is an MCP tool.

Release checklist: bench --live baseline recorded (bench/results.jsonl) — hard metrics all zero, eval 5/5, --compare no regressions.